file="/home/CAMPUS/lmh12014/github/Climate Change Narratives/Leah/856924.csv"
import=read.csv(file)
plot(TMAX~DATE, import)
import$TMAX[import$TMAX==-9999] = NA
import$TMIN[import$TMIN==-9999] = NA
plot(TMAX~DATE, import[import$DATE<19131231,], ty='l')
strDates <- as.character(import$DATE)
head(strDates)
## [1] "18911001" "18911014" "18911028" "18911101" "18911102" "18911118"
import$NewDate <- as.Date(strDates, "%Y%m%d")
plot(TMAX~NewDate, import[import$DATE<19130102,], ty='l')
unique(import$STATION_NAME)
## [1] GAINESVILLE GA US
## [2] ATLANTA HARTSFIELD INTERNATIONAL AIRPORT GA US
## 2 Levels: ATLANTA HARTSFIELD INTERNATIONAL AIRPORT GA US ...
GAINESVILLE <- subset(import, STATION_NAME=="GAINESVILLE GA US", select=c(STATION, STATION_NAME, DATE, NewDate, TMIN, TMAX, PRCP))
plot(TMAX~NewDate, GAINESVILLE, ty='l')
# Linear Model
GAINESVILLE.lm <- lm(TMAX~NewDate, data=GAINESVILLE)
summary(GAINESVILLE.lm)
##
## Call:
## lm(formula = TMAX ~ NewDate, data = GAINESVILLE)
##
## Residuals:
## Min 1Q Median 3Q Max
## -33.484 -6.602 0.974 7.283 20.482
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.139e+01 4.474e-02 478.216 < 2e-16 ***
## NewDate 2.742e-05 3.411e-06 8.037 9.46e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 8.717 on 42467 degrees of freedom
## (863 observations deleted due to missingness)
## Multiple R-squared: 0.001519, Adjusted R-squared: 0.001495
## F-statistic: 64.59 on 1 and 42467 DF, p-value: 9.455e-16
plot(TMAX~NewDate, GAINESVILLE, ty='l')
abline(coef(GAINESVILLE.lm), col='red')
# Get months
GAINESVILLE$Month = months(GAINESVILLE$NewDate)
GAINESVILLE$Month = format(as.Date(GAINESVILLE$NewDate), format = "%m")
GAINESVILLE$Year = format(GAINESVILLE$NewDate, format="%Y")
MonthlyMean = aggregate(TMAX ~ Month + Year, GAINESVILLE, mean)
MonthlyMean$YEAR = as.numeric(MonthlyMean$Year)
MonthlyMean$MONTH = as.numeric(MonthlyMean$Month)
# change mean to sd and you'll get standard deviation for each month/year.
MonthlySD = aggregate(TMAX ~ Month + Year, GAINESVILLE, sd)
MonthlySD$YEAR = as.numeric(MonthlySD$Year)
MonthlySD$MONTH = as.numeric(MonthlySD$Month)
MonthlySD$NewDate = MonthlySD$YEAR + (MonthlySD$MONTH - 1)/12
head(MonthlySD)
## Month Year TMAX YEAR MONTH NewDate
## 1 10 1891 0 1891 10 1891.750
## 2 11 1891 0 1891 11 1891.833
## 3 04 1892 NA 1892 4 1892.250
## 4 05 1892 0 1892 5 1892.333
## 5 06 1892 NA 1892 6 1892.417
## 6 07 1892 NA 1892 7 1892.500
plot(MonthlyMean$TMAX, ty='l')
plot(MonthlySD$TMAX, ty='l')
plot(TMAX~ NewDate, data=MonthlySD, ty='l')
SD.lm <- lm(TMAX~NewDate, data=MonthlySD)
summary(SD.lm)
##
## Call:
## lm(formula = TMAX ~ NewDate, data = MonthlySD)
##
## Residuals:
## Min 1Q Median 3Q Max
## -4.1790 -0.9409 0.0016 0.9276 4.5631
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 6.973553 1.977170 3.527 0.000434 ***
## NewDate -0.001477 0.001010 -1.463 0.143644
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.291 on 1405 degrees of freedom
## (16 observations deleted due to missingness)
## Multiple R-squared: 0.001521, Adjusted R-squared: 0.0008108
## F-statistic: 2.141 on 1 and 1405 DF, p-value: 0.1436
abline(coef(SD.lm), col="red")
plot(MonthlyMean$TMAX[MonthlyMean$Month=="05"], ty='l')
plot(TMAX~YEAR, data=MonthlyMean[MonthlyMean$Month=="05",], ty='l')
May.lm <- lm(TMAX~YEAR, data=MonthlyMean[MonthlyMean$Month=="05",])
summary(May.lm)
##
## Call:
## lm(formula = TMAX ~ YEAR, data = MonthlyMean[MonthlyMean$Month ==
## "05", ])
##
## Residuals:
## Min 1Q Median 3Q Max
## -3.9123 -1.1694 -0.0564 1.2383 5.3599
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 53.424629 9.944610 5.372 4.17e-07 ***
## YEAR -0.013967 0.005079 -2.750 0.00693 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.862 on 114 degrees of freedom
## Multiple R-squared: 0.06222, Adjusted R-squared: 0.054
## F-statistic: 7.564 on 1 and 114 DF, p-value: 0.006927
abline(coef(May.lm), col="red")
MonthlyMeanTMIN = aggregate(TMIN ~ Month + Year, GAINESVILLE, mean)
MonthlyMeanTMIN$YEAR = as.numeric(MonthlyMeanTMIN$Year)
head(MonthlyMeanTMIN)
## Month Year TMIN YEAR
## 1 10 1891 -1.1 1891
## 2 11 1891 -6.7 1891
## 3 04 1892 0.0 1892
## 4 05 1892 4.4 1892
## 5 06 1892 13.3 1892
## 6 08 1892 16.7 1892
plot(MonthlyMeanTMIN$TMIN, ty='l')
plot(MonthlyMeanTMIN$TMIN[MonthlyMeanTMIN$Month=="12"], ty='l')
plot(TMIN~YEAR, data=MonthlyMeanTMIN[MonthlyMeanTMIN$Month=="12",], ty='l')
Dec.lm <- lm(TMIN~YEAR, data=MonthlyMeanTMIN[MonthlyMeanTMIN$Month=="12",])
summary(Dec.lm)
##
## Call:
## lm(formula = TMIN ~ YEAR, data = MonthlyMeanTMIN[MonthlyMeanTMIN$Month ==
## "12", ])
##
## Residuals:
## Min 1Q Median 3Q Max
## -4.7557 -1.5152 0.0154 1.2723 5.2091
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -25.598861 11.322781 -2.261 0.0256 *
## YEAR 0.013487 0.005789 2.330 0.0215 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 2.197 on 118 degrees of freedom
## Multiple R-squared: 0.04397, Adjusted R-squared: 0.03587
## F-statistic: 5.427 on 1 and 118 DF, p-value: 0.02152
abline(coef(Dec.lm), col="red")
PRCP_mean = mean(GAINESVILLE$PRCP, na.rm=T)
plot(PRCP~NewDate, data=GAINESVILLE)
abline(h=PRCP_mean, col="blue")
import$PRCP[import$PRCP==-9999] = NA
plot(TMAX~DATE, import, ty='l')
YearlySum = aggregate(PRCP ~ Year, GAINESVILLE, sum)
YearlyMean = mean(YearlySum$PRCP)
YearlySum$Departure = YearlyMean - YearlySum$PRCP
YearlySum$YEAR = as.numeric(YearlySum$Year)
plot(PRCP~YEAR, data=YearlySum, las=1, ty="l")
abline(h=YearlyMean, col="blue")
lines(Departure ~ YEAR, data=YearlySum, col="red")
plot(MonthlyMean$TMAX[MonthlyMean$Month=="01"], ty='l')
plot(TMAX~YEAR, data=MonthlyMean[MonthlyMean$Month=="01",], ty='l')
Jan.lm <- lm(TMAX~YEAR, data=MonthlyMean[MonthlyMean$Month=="01",])
summary(Jan.lm)
##
## Call:
## lm(formula = TMAX ~ YEAR, data = MonthlyMean[MonthlyMean$Month ==
## "01", ])
##
## Residuals:
## Min 1Q Median 3Q Max
## -6.9331 -1.8199 0.2279 1.8629 9.0337
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 22.255331 13.789213 1.614 0.109
## YEAR -0.005964 0.007049 -0.846 0.399
##
## Residual standard error: 2.712 on 119 degrees of freedom
## Multiple R-squared: 0.005979, Adjusted R-squared: -0.002374
## F-statistic: 0.7158 on 1 and 119 DF, p-value: 0.3992
abline(coef(Jan.lm), col="red")
plot(MonthlyMean$TMAX[MonthlyMean$Month=="02"], ty='l')
plot(TMAX~YEAR, data=MonthlyMean[MonthlyMean$Month=="02",], ty='l')
Feb.lm <- lm(TMAX~YEAR, data=MonthlyMean[MonthlyMean$Month=="02",])
summary(Feb.lm)
##
## Call:
## lm(formula = TMAX ~ YEAR, data = MonthlyMean[MonthlyMean$Month ==
## "02", ])
##
## Residuals:
## Min 1Q Median 3Q Max
## -6.3125 -1.7842 -0.2788 1.9348 10.5434
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -7.872495 14.095797 -0.558 0.578
## YEAR 0.010316 0.007205 1.432 0.155
##
## Residual standard error: 2.772 on 119 degrees of freedom
## Multiple R-squared: 0.01693, Adjusted R-squared: 0.008674
## F-statistic: 2.05 on 1 and 119 DF, p-value: 0.1548
abline(coef(Feb.lm), col="red")
plot(MonthlyMean$TMAX[MonthlyMean$Month=="03"], ty='l')
plot(TMAX~YEAR, data=MonthlyMean[MonthlyMean$Month=="03",], ty='l')
Mar.lm <- lm(TMAX~YEAR, data=MonthlyMean[MonthlyMean$Month=="03",])
summary(Mar.lm)
##
## Call:
## lm(formula = TMAX ~ YEAR, data = MonthlyMean[MonthlyMean$Month ==
## "03", ])
##
## Residuals:
## Min 1Q Median 3Q Max
## -6.3677 -1.7769 0.1607 1.6360 9.1052
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.035120 12.508201 0.003 0.998
## YEAR 0.008695 0.006393 1.360 0.176
##
## Residual standard error: 2.441 on 118 degrees of freedom
## Multiple R-squared: 0.01544, Adjusted R-squared: 0.007093
## F-statistic: 1.85 on 1 and 118 DF, p-value: 0.1764
abline(coef(Mar.lm), col="red")
plot(MonthlyMean$TMAX[MonthlyMean$Month=="04"], ty='l')
plot(TMAX~YEAR, data=MonthlyMean[MonthlyMean$Month=="04",], ty='l')
Apr.lm <- lm(TMAX~YEAR, data=MonthlyMean[MonthlyMean$Month=="04",])
summary(Apr.lm)
##
## Call:
## lm(formula = TMAX ~ YEAR, data = MonthlyMean[MonthlyMean$Month ==
## "04", ])
##
## Residuals:
## Min 1Q Median 3Q Max
## -5.6147 -1.2167 -0.1289 1.4288 7.6317
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 11.907251 10.411899 1.144 0.255
## YEAR 0.005206 0.005318 0.979 0.330
##
## Residual standard error: 1.979 on 116 degrees of freedom
## Multiple R-squared: 0.008194, Adjusted R-squared: -0.0003563
## F-statistic: 0.9583 on 1 and 116 DF, p-value: 0.3296
abline(coef(Apr.lm), col="red")
plot(MonthlyMean$TMAX[MonthlyMean$Month=="05"], ty='l')
plot(TMAX~YEAR, data=MonthlyMean[MonthlyMean$Month=="05",], ty='l')
May.lm <- lm(TMAX~YEAR, data=MonthlyMean[MonthlyMean$Month=="05",])
summary(May.lm)
##
## Call:
## lm(formula = TMAX ~ YEAR, data = MonthlyMean[MonthlyMean$Month ==
## "05", ])
##
## Residuals:
## Min 1Q Median 3Q Max
## -3.9123 -1.1694 -0.0564 1.2383 5.3599
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 53.424629 9.944610 5.372 4.17e-07 ***
## YEAR -0.013967 0.005079 -2.750 0.00693 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.862 on 114 degrees of freedom
## Multiple R-squared: 0.06222, Adjusted R-squared: 0.054
## F-statistic: 7.564 on 1 and 114 DF, p-value: 0.006927
abline(coef(May.lm), col="red")
plot(MonthlyMean$TMAX[MonthlyMean$Month=="06"], ty='l')
plot(TMAX~YEAR, data=MonthlyMean[MonthlyMean$Month=="06",], ty='l')
June.lm <- lm(TMAX~YEAR, data=MonthlyMean[MonthlyMean$Month=="06",])
summary(June.lm)
##
## Call:
## lm(formula = TMAX ~ YEAR, data = MonthlyMean[MonthlyMean$Month ==
## "06", ])
##
## Residuals:
## Min 1Q Median 3Q Max
## -4.4631 -1.3731 -0.0821 1.2418 4.9289
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 61.728197 9.952473 6.202 8.83e-09 ***
## YEAR -0.016300 0.005084 -3.206 0.00174 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.893 on 116 degrees of freedom
## Multiple R-squared: 0.0814, Adjusted R-squared: 0.07349
## F-statistic: 10.28 on 1 and 116 DF, p-value: 0.001738
abline(coef(June.lm), col="red")
plot(MonthlyMean$TMAX[MonthlyMean$Month=="07"], ty='l')
plot(TMAX~YEAR, data=MonthlyMean[MonthlyMean$Month=="07",], ty='l')
July.lm <- lm(TMAX~YEAR, data=MonthlyMean[MonthlyMean$Month=="07",])
summary(July.lm)
##
## Call:
## lm(formula = TMAX ~ YEAR, data = MonthlyMean[MonthlyMean$Month ==
## "07", ])
##
## Residuals:
## Min 1Q Median 3Q Max
## -4.1832 -1.1126 -0.0883 0.9353 5.2876
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 41.582738 8.773237 4.740 6.18e-06 ***
## YEAR -0.005394 0.004480 -1.204 0.231
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.649 on 115 degrees of freedom
## Multiple R-squared: 0.01245, Adjusted R-squared: 0.003858
## F-statistic: 1.449 on 1 and 115 DF, p-value: 0.2311
abline(coef(July.lm), col="red")
plot(MonthlyMean$TMAX[MonthlyMean$Month=="08"], ty='l')
plot(TMAX~YEAR, data=MonthlyMean[MonthlyMean$Month=="08",], ty='l')
Aug.lm <- lm(TMAX~YEAR, data=MonthlyMean[MonthlyMean$Month=="08",])
summary(Aug.lm)
##
## Call:
## lm(formula = TMAX ~ YEAR, data = MonthlyMean[MonthlyMean$Month ==
## "08", ])
##
## Residuals:
## Min 1Q Median 3Q Max
## -3.2257 -1.1544 -0.2075 1.0694 5.7887
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 42.134252 8.808153 4.784 5.15e-06 ***
## YEAR -0.005929 0.004498 -1.318 0.19
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.648 on 115 degrees of freedom
## Multiple R-squared: 0.01488, Adjusted R-squared: 0.006316
## F-statistic: 1.737 on 1 and 115 DF, p-value: 0.1901
abline(coef(Aug.lm), col="red")
plot(MonthlyMean$TMAX[MonthlyMean$Month=="09"], ty='l')
plot(TMAX~YEAR, data=MonthlyMean[MonthlyMean$Month=="09",], ty='l')
Sep.lm <- lm(TMAX~YEAR, data=MonthlyMean[MonthlyMean$Month=="09",])
summary(Sep.lm)
##
## Call:
## lm(formula = TMAX ~ YEAR, data = MonthlyMean[MonthlyMean$Month ==
## "09", ])
##
## Residuals:
## Min 1Q Median 3Q Max
## -4.0127 -1.2843 -0.1172 1.2550 5.9304
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 53.204195 10.146842 5.243 7.25e-07 ***
## YEAR -0.013128 0.005182 -2.534 0.0126 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.899 on 115 degrees of freedom
## Multiple R-squared: 0.05287, Adjusted R-squared: 0.04463
## F-statistic: 6.419 on 1 and 115 DF, p-value: 0.01264
abline(coef(Sep.lm), col="red")
plot(MonthlyMean$TMAX[MonthlyMean$Month=="10"], ty='l')
plot(TMAX~YEAR, data=MonthlyMean[MonthlyMean$Month=="10",], ty='l')
Oct.lm <- lm(TMAX~YEAR, data=MonthlyMean[MonthlyMean$Month=="10",])
summary(Oct.lm)
##
## Call:
## lm(formula = TMAX ~ YEAR, data = MonthlyMean[MonthlyMean$Month ==
## "10", ])
##
## Residuals:
## Min 1Q Median 3Q Max
## -3.9464 -1.3007 -0.0772 1.0190 7.3274
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 35.746474 10.721634 3.334 0.00116 **
## YEAR -0.006910 0.005475 -1.262 0.20949
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 2.016 on 114 degrees of freedom
## Multiple R-squared: 0.01378, Adjusted R-squared: 0.005129
## F-statistic: 1.593 on 1 and 114 DF, p-value: 0.2095
abline(coef(Oct.lm), col="red")
plot(MonthlyMean$TMAX[MonthlyMean$Month=="11"], ty='l')
plot(TMAX~YEAR, data=MonthlyMean[MonthlyMean$Month=="11",], ty='l')
Nov.lm <- lm(TMAX~YEAR, data=MonthlyMean[MonthlyMean$Month=="11",])
summary(Nov.lm)
##
## Call:
## lm(formula = TMAX ~ YEAR, data = MonthlyMean[MonthlyMean$Month ==
## "11", ])
##
## Residuals:
## Min 1Q Median 3Q Max
## -4.0269 -1.3997 -0.1126 0.9121 7.8486
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 13.824048 10.684058 1.294 0.198
## YEAR 0.001442 0.005465 0.264 0.792
##
## Residual standard error: 2.183 on 121 degrees of freedom
## Multiple R-squared: 0.0005752, Adjusted R-squared: -0.007685
## F-statistic: 0.06964 on 1 and 121 DF, p-value: 0.7923
abline(coef(Nov.lm), col="red")
plot(MonthlyMean$TMAX[MonthlyMean$Month=="12"], ty='l')
plot(TMAX~YEAR, data=MonthlyMean[MonthlyMean$Month=="12",], ty='l')
Dec.lm <- lm(TMAX~YEAR, data=MonthlyMean[MonthlyMean$Month=="12",])
summary(Dec.lm)
##
## Call:
## lm(formula = TMAX ~ YEAR, data = MonthlyMean[MonthlyMean$Month ==
## "12", ])
##
## Residuals:
## Min 1Q Median 3Q Max
## -5.7164 -1.2060 0.0194 1.4514 7.1052
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -16.348026 12.175837 -1.343 0.182
## YEAR 0.014233 0.006225 2.286 0.024 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 2.361 on 117 degrees of freedom
## Multiple R-squared: 0.04277, Adjusted R-squared: 0.03459
## F-statistic: 5.227 on 1 and 117 DF, p-value: 0.02403
abline(coef(Dec.lm), col="red")
plot(MonthlyMeanTMIN$TMIN, ty='l')
plot(MonthlyMeanTMIN$TMIN[MonthlyMeanTMIN$Month=="01"], ty='l')
plot(TMIN~YEAR, data=MonthlyMeanTMIN[MonthlyMeanTMIN$Month=="01",], ty='l')
Jan.lm <- lm(TMIN~YEAR, data=MonthlyMeanTMIN[MonthlyMeanTMIN$Month=="01",])
summary(Jan.lm)
##
## Call:
## lm(formula = TMIN ~ YEAR, data = MonthlyMeanTMIN[MonthlyMeanTMIN$Month ==
## "01", ])
##
## Residuals:
## Min 1Q Median 3Q Max
## -15.5597 -1.8136 0.0938 1.7418 7.0634
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 5.654940 15.135238 0.374 0.709
## YEAR -0.003009 0.007737 -0.389 0.698
##
## Residual standard error: 2.976 on 119 degrees of freedom
## Multiple R-squared: 0.001269, Adjusted R-squared: -0.007124
## F-statistic: 0.1512 on 1 and 119 DF, p-value: 0.6981
abline(coef(Jan.lm), col="red")
plot(MonthlyMeanTMIN$TMIN, ty='l')
plot(MonthlyMeanTMIN$TMIN[MonthlyMeanTMIN$Month=="02"], ty='l')
plot(TMIN~YEAR, data=MonthlyMeanTMIN[MonthlyMeanTMIN$Month=="02",], ty='l')
Feb.lm <- lm(TMIN~YEAR, data=MonthlyMeanTMIN[MonthlyMeanTMIN$Month=="02",])
summary(Feb.lm)
##
## Call:
## lm(formula = TMIN ~ YEAR, data = MonthlyMeanTMIN[MonthlyMeanTMIN$Month ==
## "02", ])
##
## Residuals:
## Min 1Q Median 3Q Max
## -4.9071 -1.6380 0.0457 1.6946 8.8926
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -10.331992 11.791018 -0.876 0.383
## YEAR 0.005556 0.006027 0.922 0.358
##
## Residual standard error: 2.319 on 119 degrees of freedom
## Multiple R-squared: 0.007091, Adjusted R-squared: -0.001253
## F-statistic: 0.8499 on 1 and 119 DF, p-value: 0.3585
abline(coef(Feb.lm), col="red")
plot(MonthlyMeanTMIN$TMIN, ty='l')
plot(MonthlyMeanTMIN$TMIN[MonthlyMeanTMIN$Month=="03"], ty='l')
plot(TMIN~YEAR, data=MonthlyMeanTMIN[MonthlyMeanTMIN$Month=="03",], ty='l')
Mar.lm <- lm(TMIN~YEAR, data=MonthlyMeanTMIN[MonthlyMeanTMIN$Month=="03",])
summary(Mar.lm)
##
## Call:
## lm(formula = TMIN ~ YEAR, data = MonthlyMeanTMIN[MonthlyMeanTMIN$Month ==
## "03", ])
##
## Residuals:
## Min 1Q Median 3Q Max
## -11.6900 -1.3687 -0.0931 1.5068 5.4837
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -5.354202 12.881462 -0.416 0.678
## YEAR 0.004883 0.006583 0.742 0.460
##
## Residual standard error: 2.514 on 118 degrees of freedom
## Multiple R-squared: 0.004641, Adjusted R-squared: -0.003794
## F-statistic: 0.5502 on 1 and 118 DF, p-value: 0.4597
abline(coef(Mar.lm), col="red")
plot(MonthlyMeanTMIN$TMIN, ty='l')
plot(MonthlyMeanTMIN$TMIN[MonthlyMeanTMIN$Month=="04"], ty='l')
plot(TMIN~YEAR, data=MonthlyMeanTMIN[MonthlyMeanTMIN$Month=="04",], ty='l')
Apr.lm <- lm(TMIN~YEAR, data=MonthlyMeanTMIN[MonthlyMeanTMIN$Month=="04",])
summary(Apr.lm)
##
## Call:
## lm(formula = TMIN ~ YEAR, data = MonthlyMeanTMIN[MonthlyMeanTMIN$Month ==
## "04", ])
##
## Residuals:
## Min 1Q Median 3Q Max
## -7.7591 -1.0139 -0.2238 1.0462 4.0327
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -13.586596 9.144706 -1.486 0.1400
## YEAR 0.011282 0.004672 2.415 0.0173 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.765 on 117 degrees of freedom
## Multiple R-squared: 0.04747, Adjusted R-squared: 0.03932
## F-statistic: 5.83 on 1 and 117 DF, p-value: 0.0173
abline(coef(Apr.lm), col="red")
plot(MonthlyMeanTMIN$TMIN, ty='l')
plot(MonthlyMeanTMIN$TMIN[MonthlyMeanTMIN$Month=="05"], ty='l')
plot(TMIN~YEAR, data=MonthlyMeanTMIN[MonthlyMeanTMIN$Month=="05",], ty='l')
May.lm <- lm(TMIN~YEAR, data=MonthlyMeanTMIN[MonthlyMeanTMIN$Month=="05",])
summary(May.lm)
##
## Call:
## lm(formula = TMIN ~ YEAR, data = MonthlyMeanTMIN[MonthlyMeanTMIN$Month ==
## "05", ])
##
## Residuals:
## Min 1Q Median 3Q Max
## -7.7933 -1.1183 0.2366 1.3107 4.3248
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -11.233571 10.270192 -1.094 0.276
## YEAR 0.012382 0.005246 2.360 0.020 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.952 on 114 degrees of freedom
## Multiple R-squared: 0.04659, Adjusted R-squared: 0.03823
## F-statistic: 5.571 on 1 and 114 DF, p-value: 0.01996
abline(coef(May.lm), col="red")
plot(MonthlyMeanTMIN$TMIN, ty='l')
plot(MonthlyMeanTMIN$TMIN[MonthlyMeanTMIN$Month=="06"], ty='l')
plot(TMIN~YEAR, data=MonthlyMeanTMIN[MonthlyMeanTMIN$Month=="06",], ty='l')
June.lm <- lm(TMIN~YEAR, data=MonthlyMeanTMIN[MonthlyMeanTMIN$Month=="06",])
summary(June.lm)
##
## Call:
## lm(formula = TMIN ~ YEAR, data = MonthlyMeanTMIN[MonthlyMeanTMIN$Month ==
## "06", ])
##
## Residuals:
## Min 1Q Median 3Q Max
## -3.9133 -0.6589 0.1498 0.7478 2.7504
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -7.938339 6.728224 -1.180 0.240471
## YEAR 0.012968 0.003437 3.773 0.000255 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.28 on 116 degrees of freedom
## Multiple R-squared: 0.1093, Adjusted R-squared: 0.1016
## F-statistic: 14.24 on 1 and 116 DF, p-value: 0.0002555
abline(coef(June.lm), col="red")
plot(MonthlyMeanTMIN$TMIN, ty='l')
plot(MonthlyMeanTMIN$TMIN[MonthlyMeanTMIN$Month=="07"], ty='l')
plot(TMIN~YEAR, data=MonthlyMeanTMIN[MonthlyMeanTMIN$Month=="07",], ty='l')
July.lm <- lm(TMIN~YEAR, data=MonthlyMeanTMIN[MonthlyMeanTMIN$Month=="07",])
summary(July.lm)
##
## Call:
## lm(formula = TMIN ~ YEAR, data = MonthlyMeanTMIN[MonthlyMeanTMIN$Month ==
## "07", ])
##
## Residuals:
## Min 1Q Median 3Q Max
## -3.0031 -0.6700 0.1449 0.6093 2.4160
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -8.016157 5.292532 -1.515 0.133
## YEAR 0.014045 0.002702 5.198 8.95e-07 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9782 on 114 degrees of freedom
## Multiple R-squared: 0.1916, Adjusted R-squared: 0.1845
## F-statistic: 27.02 on 1 and 114 DF, p-value: 8.949e-07
abline(coef(July.lm), col="red")
plot(MonthlyMeanTMIN$TMIN, ty='l')
plot(MonthlyMeanTMIN$TMIN[MonthlyMeanTMIN$Month=="08"], ty='l')
plot(TMIN~YEAR, data=MonthlyMeanTMIN[MonthlyMeanTMIN$Month=="08",], ty='l')
Aug.lm <- lm(TMIN~YEAR, data=MonthlyMeanTMIN[MonthlyMeanTMIN$Month=="08",])
summary(Aug.lm)
##
## Call:
## lm(formula = TMIN ~ YEAR, data = MonthlyMeanTMIN[MonthlyMeanTMIN$Month ==
## "08", ])
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.4503 -0.6314 -0.1003 0.4928 4.8436
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -5.589492 5.370852 -1.041 0.3
## YEAR 0.012631 0.002743 4.604 1.07e-05 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.021 on 116 degrees of freedom
## Multiple R-squared: 0.1545, Adjusted R-squared: 0.1472
## F-statistic: 21.2 on 1 and 116 DF, p-value: 1.068e-05
abline(coef(Aug.lm), col="red")
plot(MonthlyMeanTMIN$TMIN, ty='l')
plot(MonthlyMeanTMIN$TMIN[MonthlyMeanTMIN$Month=="09"], ty='l')
plot(TMIN~YEAR, data=MonthlyMeanTMIN[MonthlyMeanTMIN$Month=="09",], ty='l')
Sep.lm <- lm(TMIN~YEAR, data=MonthlyMeanTMIN[MonthlyMeanTMIN$Month=="09",])
summary(Sep.lm)
##
## Call:
## lm(formula = TMIN ~ YEAR, data = MonthlyMeanTMIN[MonthlyMeanTMIN$Month ==
## "09", ])
##
## Residuals:
## Min 1Q Median 3Q Max
## -7.3018 -1.0601 0.2326 1.1300 3.8149
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -7.868924 9.236459 -0.852 0.3960
## YEAR 0.012141 0.004718 2.573 0.0113 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.757 on 116 degrees of freedom
## Multiple R-squared: 0.054, Adjusted R-squared: 0.04585
## F-statistic: 6.622 on 1 and 116 DF, p-value: 0.01133
abline(coef(Sep.lm), col="red")
plot(MonthlyMeanTMIN$TMIN, ty='l')
plot(MonthlyMeanTMIN$TMIN[MonthlyMeanTMIN$Month=="10"], ty='l')
plot(TMIN~YEAR, data=MonthlyMeanTMIN[MonthlyMeanTMIN$Month=="10",], ty='l')
Oct.lm <- lm(TMIN~YEAR, data=MonthlyMeanTMIN[MonthlyMeanTMIN$Month=="10",])
summary(Oct.lm)
##
## Call:
## lm(formula = TMIN ~ YEAR, data = MonthlyMeanTMIN[MonthlyMeanTMIN$Month ==
## "10", ])
##
## Residuals:
## Min 1Q Median 3Q Max
## -10.099 -1.073 0.128 1.525 7.369
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -34.16859 13.09634 -2.609 0.01028 *
## YEAR 0.02223 0.00669 3.324 0.00119 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 2.502 on 116 degrees of freedom
## Multiple R-squared: 0.08694, Adjusted R-squared: 0.07907
## F-statistic: 11.05 on 1 and 116 DF, p-value: 0.00119
abline(coef(Oct.lm), col="red")
plot(MonthlyMeanTMIN$TMIN, ty='l')
plot(MonthlyMeanTMIN$TMIN[MonthlyMeanTMIN$Month=="11"], ty='l')
plot(TMIN~YEAR, data=MonthlyMeanTMIN[MonthlyMeanTMIN$Month=="11",], ty='l')
Nov.lm <- lm(TMIN~YEAR, data=MonthlyMeanTMIN[MonthlyMeanTMIN$Month=="11",])
summary(Nov.lm)
##
## Call:
## lm(formula = TMIN ~ YEAR, data = MonthlyMeanTMIN[MonthlyMeanTMIN$Month ==
## "11", ])
##
## Residuals:
## Min 1Q Median 3Q Max
## -9.2892 -1.4572 0.0237 1.4597 6.6496
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -42.359162 12.490849 -3.391 0.000940 ***
## YEAR 0.023745 0.006389 3.717 0.000307 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 2.54 on 121 degrees of freedom
## Multiple R-squared: 0.1025, Adjusted R-squared: 0.09504
## F-statistic: 13.81 on 1 and 121 DF, p-value: 0.0003072
abline(coef(Nov.lm), col="red")
plot(MonthlyMeanTMIN$TMIN, ty='l')
plot(MonthlyMeanTMIN$TMIN[MonthlyMeanTMIN$Month=="12"], ty='l')
plot(TMIN~YEAR, data=MonthlyMeanTMIN[MonthlyMeanTMIN$Month=="12",], ty='l')
Dec.lm <- lm(TMIN~YEAR, data=MonthlyMeanTMIN[MonthlyMeanTMIN$Month=="12",])
summary(Dec.lm)
##
## Call:
## lm(formula = TMIN ~ YEAR, data = MonthlyMeanTMIN[MonthlyMeanTMIN$Month ==
## "12", ])
##
## Residuals:
## Min 1Q Median 3Q Max
## -4.7557 -1.5152 0.0154 1.2723 5.2091
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -25.598861 11.322781 -2.261 0.0256 *
## YEAR 0.013487 0.005789 2.330 0.0215 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 2.197 on 118 degrees of freedom
## Multiple R-squared: 0.04397, Adjusted R-squared: 0.03587
## F-statistic: 5.427 on 1 and 118 DF, p-value: 0.02152
abline(coef(Dec.lm), col="red")
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